我需要使用混沌游戏表示来表示许多基因序列我从BoštjanCigan的博客（https://bostjan-cigan.com/chaos-game-representation-of-gene-structure-in-python/）获得了这个python代码
import collections
from collections import OrderedDict
from matplotlib import pyplot as plt
from matplotlib import cm
import pylab
import math
f = open("ensemblSeq.fa")
s1 = f.read()
data = "".join(s1.split("\n")[1:])
def count_kmers(sequence, k):
d = collections.defaultdict(int)
for i in xrange(len(data)-(k-1)):
d[sequence[i:i+k]] +=1
for key in d.keys():
if "N" in key:
del d[key]
return d
def probabilities(kmer_count, k):
probabilities = collections.defaultdict(float)
N = len(data)
for key, value in kmer_count.items():
probabilities[key] = float(value) / (N - k + 1)
return probabilities
def chaos_game_representation(probabilities, k):
array_size = int(math.sqrt(4**k))
chaos = []
for i in range(array_size):
chaos.append([0]*array_size)
maxx = array_size
maxy = array_size
posx = 1
posy = 1
for key, value in probabilities.items():
for char in key:
if char == "T":
posx += maxx / 2
elif char == "C":
posy += maxy / 2
elif char == "G":
posx += maxx / 2
posy += maxy / 2
maxx = maxx / 2
maxy /= 2
chaos[posy-1][posx-1] = value
maxx = array_size
maxy = array_size
posx = 1
posy = 1
return chaos
f3 = count_kmers(data, 3)
f4 = count_kmers(data, 4)
f3_prob = probabilities(f3, 3)
f4_prob = probabilities(f4, 4)
chaos_k3 = chaos_game_representation(f3_prob, 3)
pylab.title('Chaos game representation for 3-mers')
pylab.imshow(chaos_k3, interpolation='nearest', cmap=cm.gray_r)
pylab.show()
chaos_k4 = chaos_game_representation(f4_prob, 4)
pylab.title('Chaos game representation for 4-mers')
pylab.imshow(chaos_k4, interpolation='nearest', cmap=cm.gray_r)
pylab.show()
这段代码工作正常但我有很多序列文件我需要遍历文件夹中的每个fasta文件，并获得存储在一个文件夹中的单个图，其中图像文件的名称对应于fasta文件的名称我该怎么办？根据我的需要修改代码
我是python以及StackOverflow的新手，如果有任何错误，请忽略
提前致谢
答案 0 :(得分：0)
因此，如果要在目录中的每个文件上应用代码，执行此操作的一种非常简单的方法是调用for循环内的所有文件。我建议如下：
import collections
import os
from collections import OrderedDict
from matplotlib import pyplot as plt
from matplotlib import cm
import pylab
import math
def count_kmers(sequence, k):
d = collections.defaultdict(int)
for i in xrange(len(data)-(k-1)):
d[sequence[i:i+k]] +=1
for key in d.keys():
if "N" in key:
del d[key]
return d
def probabilities(kmer_count, k):
probabilities = collections.defaultdict(float)
N = len(data)
for key, value in kmer_count.items():
probabilities[key] = float(value) / (N - k + 1)
return probabilities
def chaos_game_representation(probabilities, k):
array_size = int(math.sqrt(4**k))
chaos = []
for i in range(array_size):
chaos.append([0]*array_size)
maxx = array_size
maxy = array_size
posx = 1
posy = 1
for key, value in probabilities.items():
for char in key:
if char == "T":
posx += maxx / 2
elif char == "C":
posy += maxy / 2
elif char == "G":
posx += maxx / 2
posy += maxy / 2
maxx = maxx / 2
maxy /= 2
chaos[posy-1][posx-1] = value
maxx = array_size
maxy = array_size
posx = 1
posy = 1
return chaos
if __name__ == "__main__":
PATH = os.getcwd()
filelist = sorted([os.path.join(PATH, f) for f in os.listdir(PATH) if f.endswith('.fa')])
for file in filelist:
f = open(file)
s1 = f.read()
data = "".join(s1.split("\n")[1:])
f3 = count_kmers(data, 3)
f4 = count_kmers(data, 4)
f3_prob = probabilities(f3, 3)
f4_prob = probabilities(f4, 4)
chaos_k3 = chaos_game_representation(f3_prob, 3)
pylab.title('Chaos game representation for 3-mers')
pylab.imshow(chaos_k3, interpolation='nearest', cmap=cm.gray_r)
pylab.savefig(os.path.splitext(file)[0]+'chaos3.png')
pylab.show()
chaos_k4 = chaos_game_representation(f4_prob, 4)
pylab.title('Chaos game representation for 4-mers')
pylab.imshow(chaos_k4, interpolation='nearest', cmap=cm.gray_r)
pylab.savefig(os.path.splitext(file)[0]+'chaos4.png')
pylab.show()
我只是绕了一圈并添加了pylab.savefig()来电。此外，我使用os从您的目录中获取文件名。它现在应该工作。